RescueME

Project Description

RescueME takes immediate action to demonstrate how an innovative data-driven, community-based, heritage-centric approach to resilience enhancement can protect European cultural heritage and landscapes while supporting the transition toward a green, cohesive, and nature-connected society. The project proposes a call for action — broadening the scope, mobilising resources, engaging stakeholders, facilitating decision-making, and enhancing the implementation of co-created and just resilience solutions to protect our common heritage.

RescueME develops, tests, and demonstrates an Actionable Framework based on the Resilient Historical Landscape (RHL) approach, complemented by data, models, methods, and tools able to assess risks and opportunities, co-develop inclusive resilience strategies, and protect European cultural heritage and cultural landscapes from climate change, disaster risk, pollution, and over-tourism. A special focus is placed on European coastal landscapes, where a large share of endangered heritage is concentrated.

Five complementary case studies — Psiloritis (Crete, Greece), Neuwerk (Hamburg, Germany), Portovenere, Cinque Terre & the Islands (Italy), València (Spain), and the city of Zadar (Croatia) — act as Resilience Landscape Laboratories (R-labscapes), validating the results and ensuring their replicability across diverse European coastal contexts.

LINKS Foundation Activities

LINKS Foundation participates as a research and technology partner, leading key work in AI-based services, geospatial data management, and augmented reality tools for cultural heritage resilience monitoring and citizen engagement.

AI-Based Hazard Mapping Services

Leading the development of AI-powered mapping models for cultural heritage resilience, leveraging Copernicus satellite data to delineate the extent of natural hazards — floods, wildfires, and landslides — and estimate their impacts on cultural heritage elements, including:

• automated hazard delineation (fire, flood, landslide) and severity mapping (fire) operationally integrated with the project’s geospatial data platform
• evolution and improvement of AI mapping services developed in the predecessor SHELTER project
• delivery of high-TRL mapping outputs directly consumable by end-users and decision-support tools

Social Media Sentiment Monitoring & Crowdsourcing

Development of two AI-powered crowdsourcing tools for the co-characterisation of landscape values and community-driven monitoring of cultural heritage assets:

• a social media data analysis module that automatically fetches, filters, and analyses social media posts (text and images) using NLP and image analysis techniques, providing sentiment analysis and characterisation of cultural heritage assets over time
• a conversational chatbot for mobile applications enabling distributed data collection on CH conditions, targeted at public administrations, volunteering organisations, and civil protection agencies

Geospatial and Interoperable Web Application Platform

Design and delivery of an interoperable geospatial Web Application Platform composed of:

• a scalable Data Lake for the storage and management of heterogeneous geospatial and non-geospatial data;
• a suite of containerized microservices implementing the developed AI tools, geospatial processing workflows, and domain-specific services;
• a system message bus enabling asynchronous communication, event-driven processing, and workflow orchestration across platform components;
• a set of REST and OGC-compliant APIs ensuring interoperability with external systems and facilitating data and service integration;
• a web-based frontend providing intuitive access to data visualization, AI-powered analytics, monitoring, and platform management.

The platform architecture supports scalable deployment, modular extensibility, secure service integration, and standards-based interoperability, enabling efficient data ingestion, processing, storage, analysis, and dissemination for end-user applications.

Augmented Reality Interface with AI-Generative Art

Development of an AR-based interface for mobile devices supporting on-site visualisation of territorial data and resilience strategies for citizens, including:

• integration of geospatial data streams (social media posts, chatbot reports, satellite hazard maps) and resilience assessments into an immersive AR experience
• generation of AI-produced paintings from historical CH imagery combined with citizens’ social media sentiment scores, creating an innovative bridge between cultural heritage, creative industries, and data-driven storytelling

Monitoring Frameworks for Cultural Landscapes

Contribution to the design of monitoring approaches for cultural landscape elements and resilience solutions, reviewing existing methodologies and integrating them with the project’s assessment framework and data sources for scalable, replicable CH monitoring across European coastal landscapes.

Funding & Dates

SDGs — Sustainable Development Goals

🏙️ Goal 11 — Sustainable Cities and Communities

Key Technologies

🤖 AI & Machine Learning for Hazard Mapping

Deep learning models trained on Copernicus satellite data to automatically delineate the extent and severity of floods, wildfires, and landslides, providing near real-time hazard mapping services that quantify impacts on cultural heritage elements.

💬 NLP & Social Media Sentiment Analysis

Natural Language Processing and image analysis techniques applied to social media data streams to characterise cultural heritage assets, detect public sentiment about local places, and support heritage monitoring and community engagement in real time.

🗄️ Geospatial Data Lake & Interoperability

An INSPIRE-compliant, GEOSS-interoperable Data Lake architecture for managing large, heterogeneous geospatial datasets across the project’s case studies, with OGC-compliant APIs, distributed file storage, a GAIA importer/mapper, and a web-based interface for end-users.

🥽 Augmented Reality & Generative AI

An AR mobile interface enabling citizens to visualise territorial resilience data on-site, enriched by AI-generated paintings that translate sentiment scores and cultural heritage imagery into novel artistic representations, connecting data, heritage, and creative industries.

🌍 Copernicus Earth Observation

Exploitation of Copernicus satellite data for both AI model training and operational hazard monitoring, integrated with in-situ data and citizen-sourced reports into a unified geospatial intelligence platform.

🤝 Crowdsourcing & Conversational Chatbot

A distributed data collection system combining a conversational AI chatbot for mobile platforms and social media monitoring, enabling communities, civil protection bodies, and local organisations to contribute real-time observations on cultural heritage conditions and hazard events.

Project Partners